library(survminer)
library(survival)
library(tidyverse)
library(DT)
PATH <- file.path(Sys.getenv("MLAB"), "projects/brcameta/exosome/4t1_brca_brain_mets/")
TCGAPATH <- file.path(Sys.getenv("CBM"),"TCGA-GDC/")
DPATH <- file.path(Sys.getenv("CBM"),"otherStudies/RNAseq/2022-06-03-DenisExosomeBrCaBrainMets/")
do_save <- TRUE
tcga_gsva <- readRDS(file.path(PATH, "data/tcga_gsva_res.rds"))
metabric_gsva <- readRDS(file.path(PATH, "data/metabric_gsva_res.rds"))
#Signatures
all_sigs <- readRDS(file.path(PATH,"data/signatures_symbol.rds"))
all_sigs <- all_sigs[lapply(all_sigs, length) > 1]
all_sigs_human <- lapply(all_sigs, babelgene::orthologs, species="mouse", human=FALSE)
all_sigs_human <- lapply(all_sigs_human, function (x) x %>% dplyr::pull(human_symbol))
Data Filtering
na_filter <- !is.na(tcga_gsva$vital_status)
missing_death_day_filter <- !((tcga_gsva$vital_status == "Dead") & is.na(tcga_gsva$days_to_death))
subtype_filter <- !is.na(tcga_gsva$subtype_selected)
data_filter <- na_filter & missing_death_day_filter & subtype_filter
tcga_gsva <- tcga_gsva[,data_filter]
Censoring: If samples are alive, then they lived at least as long as the day to their last followup. For 5 year threshold, those who died after 5 years, should be right-censored, and labeled to have lived at least as long as ‘days to death’ + 1.
pData(tcga_gsva) <- pData(tcga_gsva) %>%
rownames_to_column("ID") %>%
mutate(time = if_else(!is.na(days_to_death),days_to_death,days_to_last_follow_up)) %>%
mutate(time_5 = if_else(as.numeric(time) < 1825.0, as.numeric(time) , 1826.0)) %>%
mutate(vital_status_1 = if_else(vital_status == "Alive", 1, 2)) %>%
mutate(vital_status_5 = if_else(vital_status == "Dead" & (time_5 > 1825.0), 1, vital_status_1)) %>%
column_to_rownames("ID")
pData(metabric_gsva) <- pData(metabric_gsva) %>%
mutate(time = OS_MONTHS*30.437) %>%
mutate(time_5 = if_else(as.numeric(time) < 1825.0, as.numeric(time) , 1826.0)) %>%
mutate(vital_status_1 = if_else(OS_STATUS == "LIVING", 1, 2)) %>%
mutate(vital_status_5 = if_else(OS_STATUS == "DECEASED" & (time_5 > 1825.0), 1, vital_status_1))
tcga_threshold_ir_c <- median(exprs(tcga_gsva["ir_c_up",]) - exprs(tcga_gsva["ir_c_down"]))
tcga_threshold_is_c <- median(exprs(tcga_gsva["is_c_up",])-exprs(tcga_gsva["is_c_down",]))
tcga_threshold_ir_is <- median(exprs(tcga_gsva["ir_is_up",])-exprs(tcga_gsva["ir_is_down",]))
metabric_threshold_ir_c <- median(exprs(metabric_gsva["ir_c_up",]) - exprs(metabric_gsva["ir_c_down"]))
metabric_threshold_is_c <- median(exprs(metabric_gsva["is_c_up",])-exprs(metabric_gsva["is_c_down",]))
metabric_threshold_ir_is <- median(exprs(metabric_gsva["ir_is_up",])-exprs(metabric_gsva["ir_is_down",]))
tcga_threshold_ir_c_up <- median(exprs(tcga_gsva["ir_c_up",]))
tcga_threshold_is_c_up <- median(exprs(tcga_gsva["is_c_up",]))
tcga_threshold_ir_is_up <- median(exprs(tcga_gsva["ir_is_up",]))
metabric_threshold_ir_c_up <- median(exprs(metabric_gsva["ir_c_up",]))
metabric_threshold_is_c_up <- median(exprs(metabric_gsva["is_c_up",]))
metabric_threshold_ir_is_up <- median(exprs(metabric_gsva["ir_is_up",]))
Adding GSVA data
tcga_gsva$ir_c <- t(exprs(tcga_gsva["ir_c_up",]) - exprs(tcga_gsva["ir_c_down"]))
tcga_gsva$is_c <- t(exprs(tcga_gsva["is_c_up",])-exprs(tcga_gsva["is_c_down",]))
tcga_gsva$ir_is <- t(exprs(tcga_gsva["ir_is_up",])-exprs(tcga_gsva["ir_is_down",]))
tcga_gsva$ir_c_stat <- with(tcga_gsva, ifelse(tcga_gsva$ir_c <= tcga_threshold_ir_c, "low", "high"))
tcga_gsva$is_c_stat <- with(tcga_gsva, ifelse(tcga_gsva$is_c <= tcga_threshold_is_c, "low", "high"))
tcga_gsva$ir_is_stat <- with(tcga_gsva, ifelse(tcga_gsva$ir_is <= tcga_threshold_ir_is, "low", "high"))
tcga_gsva$ir_c_up <- t(exprs(tcga_gsva["ir_c_up",]))
tcga_gsva$is_c_up <- t(exprs(tcga_gsva["is_c_up",]))
tcga_gsva$ir_is_up <- t(exprs(tcga_gsva["ir_is_up",]))
tcga_gsva$ir_c_up_stat <- with(tcga_gsva, ifelse(tcga_gsva$ir_c_up <= tcga_threshold_ir_c_up, "low", "high"))
tcga_gsva$is_c_up_stat <- with(tcga_gsva, ifelse(tcga_gsva$is_c_up <= tcga_threshold_is_c_up, "low", "high"))
tcga_gsva$ir_is_up_stat <- with(tcga_gsva, ifelse(tcga_gsva$ir_is_up <= tcga_threshold_ir_is_up, "low", "high"))
metabric_gsva$ir_c <- t(exprs(metabric_gsva["ir_c_up",]) - exprs(metabric_gsva["ir_c_down"]))
metabric_gsva$is_c <- t(exprs(metabric_gsva["is_c_up",])-exprs(metabric_gsva["is_c_down",]))
metabric_gsva$ir_is <- t(exprs(metabric_gsva["ir_is_up",])-exprs(metabric_gsva["ir_is_down",]))
metabric_gsva$ir_c_stat <- with(metabric_gsva, ifelse(metabric_gsva$ir_c <= metabric_threshold_ir_c, "low", "high"))
metabric_gsva$is_c_stat <- with(metabric_gsva, ifelse(metabric_gsva$is_c <= metabric_threshold_is_c, "low", "high"))
metabric_gsva$ir_is_stat <- with(metabric_gsva, ifelse(metabric_gsva$ir_is <= metabric_threshold_ir_is, "low", "high"))
metabric_gsva$ir_c_up <- t(exprs(metabric_gsva["ir_c_up",]))
metabric_gsva$is_c_up <- t(exprs(metabric_gsva["is_c_up",]))
metabric_gsva$ir_is_up <- t(exprs(metabric_gsva["ir_is_up",]))
metabric_gsva$ir_c_up_stat <- with(metabric_gsva, ifelse(metabric_gsva$ir_c_up <= metabric_threshold_ir_c_up, "low", "high"))
metabric_gsva$is_c_up_stat <- with(metabric_gsva, ifelse(metabric_gsva$is_c_up <= metabric_threshold_is_c_up, "low", "high"))
metabric_gsva$ir_is_up_stat <- with(metabric_gsva, ifelse(metabric_gsva$ir_is_up <= metabric_threshold_ir_is_up, "low", "high"))
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time), tcga_gsva$vital_status_1) ~ tcga_gsva$ir_c_up_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time_5), tcga_gsva$vital_status_5) ~ tcga_gsva$ir_c_up_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time), metabric_gsva$vital_status_1) ~ metabric_gsva$ir_c_up_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time_5), metabric_gsva$vital_status_5) ~ metabric_gsva$ir_c_up_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time), tcga_gsva$vital_status_1) ~ tcga_gsva$ir_c_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time_5), tcga_gsva$vital_status_5) ~ tcga_gsva$ir_c_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time), metabric_gsva$vital_status_1) ~ metabric_gsva$ir_c_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time_5), metabric_gsva$vital_status_5) ~ metabric_gsva$ir_c_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time), tcga_gsva$vital_status_1) ~ tcga_gsva$is_c_up_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time_5), tcga_gsva$vital_status_5) ~ tcga_gsva$is_c_up_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time), metabric_gsva$vital_status_1) ~ metabric_gsva$is_c_up_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time_5), metabric_gsva$vital_status_5) ~ metabric_gsva$is_c_up_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time), tcga_gsva$vital_status_1) ~ tcga_gsva$is_c_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time_5), tcga_gsva$vital_status_5) ~ tcga_gsva$is_c_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time), metabric_gsva$vital_status_1) ~ metabric_gsva$is_c_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time_5), metabric_gsva$vital_status_5) ~ metabric_gsva$is_c_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time), tcga_gsva$vital_status_1) ~ tcga_gsva$ir_is_up_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time_5), tcga_gsva$vital_status_5) ~ tcga_gsva$ir_is_up_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time), metabric_gsva$vital_status_1) ~ metabric_gsva$ir_is_up_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time_5), metabric_gsva$vital_status_5) ~ metabric_gsva$ir_is_up_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time), tcga_gsva$vital_status_1) ~ tcga_gsva$ir_is_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva$time_5), tcga_gsva$vital_status_5) ~ tcga_gsva$ir_is_stat),
data = tcga_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time), metabric_gsva$vital_status_1) ~ metabric_gsva$ir_is_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva$time_5), metabric_gsva$vital_status_5) ~ metabric_gsva$ir_is_stat),
data = metabric_gsva,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'METABRIC w/ 5-year threshold')
Thresholds
tcga_basal_filter <- tcga_gsva$subtype_selected == "BRCA.Basal"
tcga_gsva_basal <- tcga_gsva[,tcga_basal_filter]
metabric_basal_filter <- metabric_gsva$Pam50_SUBTYPE == "Basal"
metabric_gsva_basal <- metabric_gsva[,metabric_basal_filter]
tcga_threshold_ir_c <- median(exprs(tcga_gsva_basal["ir_c_up",])-exprs(tcga_gsva_basal["ir_c_down",]))
tcga_threshold_is_c <- median(exprs(tcga_gsva_basal["is_c_up",])-exprs(tcga_gsva_basal["is_c_down",]))
tcga_threshold_ir_is <- median(exprs(tcga_gsva_basal["ir_is_up",])-exprs(tcga_gsva_basal["ir_is_down",]))
metabric_threshold_ir_c <- median(exprs(metabric_gsva_basal["ir_c_up",])-exprs(metabric_gsva_basal["ir_c_down",]))
metabric_threshold_is_c <- median(exprs(metabric_gsva_basal["is_c_up",])-exprs(metabric_gsva_basal["is_c_down",]))
metabric_threshold_ir_is <- median(exprs(metabric_gsva_basal["ir_is_up",])-exprs(metabric_gsva_basal["ir_is_down",]))
tcga_threshold_ir_c_up <- median(exprs(tcga_gsva_basal["ir_c_up",]))
tcga_threshold_is_c_up <- median(exprs(tcga_gsva_basal["is_c_up",]))
tcga_threshold_ir_is_up <- median(exprs(tcga_gsva_basal["ir_is_up",]))
metabric_threshold_ir_c_up <- median(exprs(metabric_gsva_basal["ir_c_up",]))
metabric_threshold_is_c_up <- median(exprs(metabric_gsva_basal["is_c_up",]))
metabric_threshold_ir_is_up <- median(exprs(metabric_gsva_basal["ir_is_up",]))
Adding GSVA data
tcga_gsva_basal$ir_c <- t(exprs(tcga_gsva_basal["ir_c_up",])-exprs(tcga_gsva_basal["ir_c_down",]))
tcga_gsva_basal$is_c <- t(exprs(tcga_gsva_basal["is_c_up",])-exprs(tcga_gsva_basal["is_c_down",]))
tcga_gsva_basal$ir_is <- t(exprs(tcga_gsva_basal["ir_is_up",])-exprs(tcga_gsva_basal["ir_is_down",]))
metabric_gsva_basal$ir_c <- t(exprs(metabric_gsva_basal["ir_c_up",])-exprs(metabric_gsva_basal["ir_c_down",]))
metabric_gsva_basal$is_c <- t(exprs(metabric_gsva_basal["is_c_up",])-exprs(metabric_gsva_basal["is_c_down",]))
metabric_gsva_basal$ir_is <- t(exprs(metabric_gsva_basal["ir_is_up",])-exprs(metabric_gsva_basal["ir_is_down",]))
tcga_gsva_basal$ir_c_up <- t(exprs(tcga_gsva_basal["ir_c_up",]))
tcga_gsva_basal$is_c_up <- t(exprs(tcga_gsva_basal["is_c_up",]))
tcga_gsva_basal$ir_is_up <- t(exprs(tcga_gsva_basal["ir_is_up",]))
metabric_gsva_basal$ir_c_up <- t(exprs(metabric_gsva_basal["ir_c_up",]))
metabric_gsva_basal$is_c_up <- t(exprs(metabric_gsva_basal["is_c_up",]))
metabric_gsva_basal$ir_is_up <- t(exprs(metabric_gsva_basal["ir_is_up",]))
tcga_gsva_basal$ir_c_stat <- with(tcga_gsva_basal, ifelse(tcga_gsva_basal$ir_c <= tcga_threshold_ir_c, "low", "high"))
tcga_gsva_basal$is_c_stat <- with(tcga_gsva_basal, ifelse(tcga_gsva_basal$is_c <= tcga_threshold_is_c, "low", "high"))
tcga_gsva_basal$ir_is_stat <- with(tcga_gsva_basal, ifelse(tcga_gsva_basal$ir_is <= tcga_threshold_ir_is, "low", "high"))
tcga_gsva_basal$ir_c_up_stat <- with(tcga_gsva_basal, ifelse(tcga_gsva_basal$ir_c_up <= tcga_threshold_ir_c_up, "low", "high"))
tcga_gsva_basal$is_c_up_stat <- with(tcga_gsva_basal, ifelse(tcga_gsva_basal$is_c_up <= tcga_threshold_is_c_up, "low", "high"))
tcga_gsva_basal$ir_is_up_stat <- with(tcga_gsva_basal, ifelse(tcga_gsva_basal$ir_is_up <= tcga_threshold_ir_is_up, "low", "high"))
metabric_gsva_basal$ir_c_stat <- with(metabric_gsva_basal, ifelse(metabric_gsva_basal$ir_c <= metabric_threshold_ir_c, "low", "high"))
metabric_gsva_basal$is_c_stat <- with(metabric_gsva_basal, ifelse(metabric_gsva_basal$is_c <= metabric_threshold_is_c, "low", "high"))
metabric_gsva_basal$ir_is_stat <- with(metabric_gsva_basal, ifelse(metabric_gsva_basal$ir_is <= metabric_threshold_ir_is, "low", "high"))
metabric_gsva_basal$ir_c_up_stat <- with(metabric_gsva_basal, ifelse(metabric_gsva_basal$ir_c_up <= metabric_threshold_ir_c_up, "low", "high"))
metabric_gsva_basal$is_c_up_stat <- with(metabric_gsva_basal, ifelse(metabric_gsva_basal$is_c_up <= metabric_threshold_is_c_up, "low", "high"))
metabric_gsva_basal$ir_is_up_stat <- with(metabric_gsva_basal, ifelse(metabric_gsva_basal$ir_is_up <= metabric_threshold_ir_is_up, "low", "high"))
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time), tcga_gsva_basal$vital_status_1) ~ tcga_gsva_basal$ir_c_up_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time_5), tcga_gsva_basal$vital_status_5) ~ tcga_gsva_basal$ir_c_up_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time), metabric_gsva_basal$vital_status_1) ~ metabric_gsva_basal$ir_c_up_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time_5), metabric_gsva_basal$vital_status_5) ~ metabric_gsva_basal$ir_c_up_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time), tcga_gsva_basal$vital_status_1) ~ tcga_gsva_basal$ir_c_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time_5), tcga_gsva_basal$vital_status_5) ~ tcga_gsva_basal$ir_c_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time), metabric_gsva_basal$vital_status_1) ~ metabric_gsva_basal$ir_c_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time_5), metabric_gsva_basal$vital_status_5) ~ metabric_gsva_basal$ir_c_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time), tcga_gsva_basal$vital_status_1) ~ tcga_gsva_basal$is_c_up_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time_5), tcga_gsva_basal$vital_status_5) ~ tcga_gsva_basal$is_c_up_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time), metabric_gsva_basal$vital_status_1) ~ metabric_gsva_basal$is_c_up_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time_5), metabric_gsva_basal$vital_status_5) ~ metabric_gsva_basal$is_c_up_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time), tcga_gsva_basal$vital_status_1) ~ tcga_gsva_basal$is_c_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time_5), tcga_gsva_basal$vital_status_5) ~ tcga_gsva_basal$is_c_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time), metabric_gsva_basal$vital_status_1) ~ metabric_gsva_basal$is_c_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time_5), metabric_gsva_basal$vital_status_5) ~ metabric_gsva_basal$is_c_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time), tcga_gsva_basal$vital_status_1) ~ tcga_gsva_basal$ir_is_up_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title='TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time_5), tcga_gsva_basal$vital_status_5) ~ tcga_gsva_basal$ir_is_up_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time), metabric_gsva_basal$vital_status_1) ~ metabric_gsva_basal$ir_is_up_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time_5), metabric_gsva_basal$vital_status_5) ~ metabric_gsva_basal$ir_is_up_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time), tcga_gsva_basal$vital_status_1) ~ tcga_gsva_basal$ir_is_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title='TCGA')
ggsurvplot(
fit = survfit(Surv(as.numeric(tcga_gsva_basal$time_5), tcga_gsva_basal$vital_status_5) ~ tcga_gsva_basal$ir_is_stat),
data = tcga_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'TCGA w/ 5-year threshold')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time), metabric_gsva_basal$vital_status_1) ~ metabric_gsva_basal$ir_is_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric')
ggsurvplot(
fit = survfit(Surv(as.numeric(metabric_gsva_basal$time_5), metabric_gsva_basal$vital_status_5) ~ metabric_gsva_basal$ir_is_stat),
data = metabric_gsva_basal,
xlab = "Days",
ylab = "Overall survival probability",
conf.int = TRUE,
pval = TRUE,
title = 'Metabric w/ 5-year threshold')
TCGA
pData(tcga_gsva)$subtype_selected <- relevel(factor(pData(tcga_gsva)$subtype_selected), "BRCA.Normal")
tcga.cox1 <- coxph(Surv(as.numeric(time), vital_status_1) ~ subtype_selected , data=pData(tcga_gsva))
tcga.cox2 <- coxph(Surv(as.numeric(time), vital_status_1) ~ ir_is + subtype_selected , data=pData(tcga_gsva))
anova(tcga.cox1, tcga.cox2)
summary(tcga.cox2)
## Call:
## coxph(formula = Surv(as.numeric(time), vital_status_1) ~ ir_is +
## subtype_selected, data = pData(tcga_gsva))
##
## n= 1208, number of events= 199
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ir_is 0.3748 1.4547 0.1705 2.198 0.02796 *
## subtype_selectedBRCA.Basal -0.6507 0.5217 0.2457 -2.649 0.00808 **
## subtype_selectedBRCA.Her2 -0.1176 0.8891 0.2848 -0.413 0.67974
## subtype_selectedBRCA.LumA -0.8958 0.4083 0.1903 -4.707 2.51e-06 ***
## subtype_selectedBRCA.LumB -0.3552 0.7011 0.2325 -1.528 0.12658
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## ir_is 1.4547 0.6874 1.0414 2.0321
## subtype_selectedBRCA.Basal 0.5217 1.9170 0.3223 0.8443
## subtype_selectedBRCA.Her2 0.8891 1.1248 0.5088 1.5537
## subtype_selectedBRCA.LumA 0.4083 2.4493 0.2812 0.5929
## subtype_selectedBRCA.LumB 0.7011 1.4264 0.4445 1.1057
##
## Concordance= 0.607 (se = 0.025 )
## Likelihood ratio test= 33.12 on 5 df, p=4e-06
## Wald test = 34.46 on 5 df, p=2e-06
## Score (logrank) test = 36.28 on 5 df, p=8e-07
Metabric
pData(metabric_gsva)$Pam50_SUBTYPE <- relevel(factor(pData(metabric_gsva)$Pam50_SUBTYPE), "Normal")
metabric.cox1 <- coxph(Surv(as.numeric(time), vital_status_1) ~ Pam50_SUBTYPE , data=pData(metabric_gsva))
metabric.cox2 <- coxph(Surv(as.numeric(time), vital_status_1) ~ ir_is + Pam50_SUBTYPE , data=pData(metabric_gsva))
anova(metabric.cox1, metabric.cox2)
summary(metabric.cox2)
## Call:
## coxph(formula = Surv(as.numeric(time), vital_status_1) ~ ir_is +
## Pam50_SUBTYPE, data = pData(metabric_gsva))
##
## n= 1980, number of events= 1143
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ir_is 0.13762 1.14754 0.07288 1.888 0.058967 .
## Pam50_SUBTYPEBasal 0.14860 1.16021 0.12897 1.152 0.249236
## Pam50_SUBTYPEHer2 0.45151 1.57068 0.12873 3.507 0.000453 ***
## Pam50_SUBTYPELumA -0.05352 0.94789 0.11374 -0.471 0.637988
## Pam50_SUBTYPELumB 0.39747 1.48805 0.11622 3.420 0.000626 ***
## Pam50_SUBTYPENC 0.60061 1.82323 0.45912 1.308 0.190813
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## ir_is 1.1475 0.8714 0.9948 1.324
## Pam50_SUBTYPEBasal 1.1602 0.8619 0.9011 1.494
## Pam50_SUBTYPEHer2 1.5707 0.6367 1.2204 2.021
## Pam50_SUBTYPELumA 0.9479 1.0550 0.7585 1.185
## Pam50_SUBTYPELumB 1.4881 0.6720 1.1849 1.869
## Pam50_SUBTYPENC 1.8232 0.5485 0.7414 4.484
##
## Concordance= 0.576 (se = 0.009 )
## Likelihood ratio test= 50.03 on 6 df, p=5e-09
## Wald test = 50.78 on 6 df, p=3e-09
## Score (logrank) test = 51.47 on 6 df, p=2e-09